Comparing the usefulness of real-time driving aids in a connected environment during mandatory and discretionary lane-changing manoeuvres. (December 2020)

• Record Type: Journal Article
• Authors: Ali, Yasir; Bliemer, Michiel C.J.; Zheng, Zuduo; Haque, Md. Mazharul
• Is Part Of: Transportation research. Volume 121(2020)
• Publication Date: 2020-12
• Subjects: Mandatory lane-changing -- Discretionary lane-changing -- Driving aids -- Connected environment -- Advanced driving simulator -- Braking -- Crash risk; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2020.102871
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Investigation of effectiveness of driving aids during lane-changing manoeuvres. Observations of mandatory and discretionary lane-changing in advanced driving simulator. Main benefit from driving aids during mandatory lane-changing. Impact of communication impairment is more pronounced during mandatory lane-changing. Abstract: Lane-changing manoeuvre is one of the risky manoeuvres performed by drivers either to reach the planned destination (i.e., mandatory lane-changing; MLC) or to achieve better driving conditions (i.e., discretionary lane-changing; DLC). Essentially both lane-changing types require the driver to acquire surrounding traffic information for efficient and safe lane-changing decisions. However, this does not discount the fact that both these lane-changings are fundamentally different from each other as the urgency of lane-changing is much higher during MLC compared to DLC. Real-time driving aids in a connected environment promise to assist during the lane-changing decision-making process, but the differential effectiveness (or usefulness) of real-time driving aids in a connected environment for these two lane-changing types remains unexplored due to the novelty of a connected environment and the consequent scarcity of data. To fill this research gap, this study collected lane-changing data from 78 participants who performed MLC and DLC in the CARRS-Q Advanced Driving Simulator. Participants were asked to drive in three randomised driving conditions: baseline condition (without driving aids), real-time driving aids in a connected environment with perfect communication, and delayed driving aids in a connected environment. While surrogate measures of safety are analysed and compared using descriptive statistics, a hybrid framework of data mining and classical statistical modelling is employed to examine the usefulness of the real-time driving aids in a connected environment for two lane-changing types. We find that the crash risk associated with MLC is significantly reduced in the driving conditions providing driving aids compared to that of DLC. Results also reveal that the probability of engaging in a hard-braking event decreases for both the lane-changing types in the presence of real-time driving aids in the connected environment driving conditions, but a higher decrease in magnitude is found for MLC. Age and gender-related differential impact have been observed where young and male drivers have a higher possibility of engaging in a hard-braking event when driving without driving aids, but the presence of real-time driving aids reduces such risk. This study concludes that the usefulness (or effectiveness) of the real-time driving aids in a connected environment is a function of the urgency of a task, which is evidently higher during MLC, thus providing the maximum advantage during MLC.